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SAP Business One Order-to-Cash MCP Server

SAP Business One Order-to-Cash MCP Server

by parmarnaresh86
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Remote

analyze_abc_xyz

Categorize items using ABC revenue ranking and XYZ demand variability to guide stock holding and replenishment decisions.

Instructions

ABC-XYZ inventory classification. ABC ranks items by cumulative revenue contribution (A=top 80%, B=next 15%, C=bottom 5%). XYZ scores demand variability by coefficient of variation (X=stable, Y=variable, Z=erratic). Useful for prioritising stock holding and replenishment policies.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "analyze_abc_xyz"
  }
}

Input Schema

NameRequiredDescriptionDefault
topNNoMax items to return (default 300)
historyMonthsNoMonths of sales history to use (default 12, max 24)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the burden of behavioral disclosure. It does well by explaining the exact thresholds and scoring logic: A=top 80%, B=next 15%, C=bottom 5%, and XYZ based on coefficient of variation. It does not explicitly state that the tool is read-only or describe output format, but the analytic, non-mutating nature is strongly implied.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three tight, information-dense sentences with no filler. It front-loads the core purpose, then provides essential methodological context and a brief application note.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a low-complexity, read-only analysis tool with two optional parameters, the description is nearly complete: it explains the classification scheme and intended use. The main remaining gaps are the exact return shape and an explicit statement that no data is mutated, but these are minor given the nature of the tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%—both topN and historyMonths are fully described in the input schema. The tool description adds no parameter-specific detail beyond what the schema already provides, so the baseline of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a precise statement—'ABC-XYZ inventory classification'—and then gives exact definitions for each class, making it unmistakable what the tool does. This clearly distinguishes it from sibling tools like segment_customers_rfm or analyze_revenue_concentration by specifying method and resource.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description includes a useful purpose statement—'prioritising stock holding and replenishment policies'—which implies when it would be used. However, it never explicitly contrasts this tool with alternatives like calc_reorder_point, detect_stockout, or forecast_item_demand, so the agent must infer when this is the right choice.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Deploy Server

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